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Copy file name to clipboardExpand all lines: docs/en/connector-v2/source/Jdbc.md
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| partition_column | String | No | - | The column name for split data. |
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| partition_upper_bound | Long | No | - | The partition_column max value for scan, if not set SeaTunnel will query database get max value. |
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| partition_lower_bound | Long | No | - | The partition_column min value for scan, if not set SeaTunnel will query database get min value. |
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| partition_num | Int | No | job parallelism | Not recommended for use, The correct approach is to control the number of split through `split.size`<br/> How many splits do we need to split into, only support positive integer. default value is job parallelism. |
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| partition_num | Int | No | job parallelism | Not recommended for use, The correct approach is to control the number of split through `split.size`<br/> **Note:** This parameter takes effect only when using the `query` parameter. It does not take effect when using the `table_path` parameter.|
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| decimal_type_narrowing | Boolean | No | true | Decimal type narrowing, if true, the decimal type will be narrowed to the int or long type if without loss of precision. Only support for Oracle at now. Please refer to `decimal_type_narrowing` below |
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| use_select_count | Boolean | No | false | Use select count for table count rather then other methods in dynamic chunk split stage. This is currently only available for jdbc-oracle.In this scenario, select count directly is used when it is faster to update statistics using sql from analysis table |
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| skip_analyze | Boolean | No | false | Skip the analysis of table count in dynamic chunk split stage. This is currently only available for jdbc-oracle.In this scenario, you schedule analysis table sql to update related table statistics periodically or your table data does not change frequently |
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| table_path | String | No | - | The path to the full path of table, you can use this configuration instead of `query`. <br/>examples: <br/>`- mysql: "testdb.table1" `<br/>`- oracle: "test_schema.table1" `<br/>`- sqlserver: "testdb.test_schema.table1"` <br/>`- postgresql: "testdb.test_schema.table1"` <br/>`- iris: "test_schema.table1"`|
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| table_list | Array | No | - | The list of tables to be read, you can use this configuration instead of `table_path`|
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| where_condition | String | No | - | Common row filter conditions for all tables/queries, must start with `where`. for example `where id > 100`|
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| split.size | Int | No | 8096 | How many rows in one split, captured tables are split into multiple splits when read of table. |
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| split.size | Int | No | 8096 | How many rows in one split, captured tables are split into multiple splits when read of table. **Note**: This parameter takes effect only when using the `table_path` parameter. It does not take effect when using the `query` parameter. |
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| split.even-distribution.factor.lower-bound | Double | No | 0.05 | Not recommended for use.<br/> The lower bound of the chunk key distribution factor. This factor is used to determine whether the table data is evenly distributed. If the distribution factor is calculated to be greater than or equal to this lower bound (i.e., (MAX(id) - MIN(id) + 1) / row count), the table chunks would be optimized for even distribution. Otherwise, if the distribution factor is less, the table will be considered as unevenly distributed and the sampling-based sharding strategy will be used if the estimated shard count exceeds the value specified by `sample-sharding.threshold`. The default value is 0.05. |
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| split.even-distribution.factor.upper-bound | Double | No | 100 | Not recommended for use.<br/> The upper bound of the chunk key distribution factor. This factor is used to determine whether the table data is evenly distributed. If the distribution factor is calculated to be less than or equal to this upper bound (i.e., (MAX(id) - MIN(id) + 1) / row count), the table chunks would be optimized for even distribution. Otherwise, if the distribution factor is greater, the table will be considered as unevenly distributed and the sampling-based sharding strategy will be used if the estimated shard count exceeds the value specified by `sample-sharding.threshold`. The default value is 100.0. |
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| split.sample-sharding.threshold | Int | No | 1000 | This configuration specifies the threshold of estimated shard count to trigger the sample sharding strategy. When the distribution factor is outside the bounds specified by `chunk-key.even-distribution.factor.upper-bound` and `chunk-key.even-distribution.factor.lower-bound`, and the estimated shard count (calculated as approximate row count / chunk size) exceeds this threshold, the sample sharding strategy will be used. This can help to handle large datasets more efficiently. The default value is 1000 shards. |
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password = "123456"
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query = "select * from type_bin"
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partition_column = "id"
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split.size = 10000
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partition_num = 10 # Replace split.size with partition_num
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